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AI Tool Comparison

Comparing as AI Code Generation & Autocomplete
Google Gemini API vs Augment Code

Google Gemini API

Google Gemini API

VS
Augment Code

Augment Code

Verdict by Category

Detailed category analysis is not available for this comparison.
View Google Gemini API View Augment Code

Detailed Comparison

Feature
Google Gemini API
Augment Code
Pricing
FreemiumThe Gemini API uses a three-tier structure. Free is for developers and small projects, offering limited access to select models with free input and output tokens, Google AI Studio access, and no billing account required, though content is used to improve Google's products. Paid unlocks higher rate limits for production, context caching, the Batch API (roughly 50% cost reduction), access to Google's most advanced models, and a guarantee that content is not used to improve Google's products. Pricing is billed per million tokens and varies by model: for example, Gemini 3.1 Pro Preview costs $2.00 input and $12.00 output per million tokens for prompts under 200K tokens, while cost-efficient options like Gemini 3.5 Flash-Lite start as low as $0.30 input and $2.50 output per million tokens, with additional Flex and Priority billing modes available for different latency and cost tradeoffs. Enterprise is for large-scale deployments through the Gemini Enterprise Agent Platform, adding dedicated support channels, advanced security and compliance certifications (HIPAA, SOC 2, FedRAMP), provisioned throughput, volume-based discounts, and MLOps tooling, available by contacting Google's sales team.
PaidAugment Code uses a usage-based pricing model with two tiers. The Business plan costs $100/month flat for up to 50 seats. This includes $100 of pooled monthly usage across LLM inference (billed at provider list price + 40% service fee), Context Engine API calls, and Cosmos compute. Usage is shared across the whole team. Top-ups are available pay-as-you-go at any time; top-ups expire 12 months after purchase. The Enterprise plan has custom pricing for teams over 50 seats. It adds custom usage limits and top-up rates, volume-based annual discounts, SSO/OIDC/SCIM, Customer Managed Encryption Keys (CMEK), ISO/IEC 42001 compliance, SIEM integration, data residency options, granular audit trails, multi-region compute, unlimited concurrent sessions, and a dedicated customer success manager with priority support. All paid plans include a guarantee of no AI training on customer data. A 7-day free trial is available. Previously Augment charged $60/active user/month under a named-seat model before switching to flat/usage-based pricing in October 2025.
Categories
AI Developer APIs & PlatformsAI Coding Assistants
AI Coding AssistantsAI Productivity ToolsAI Developer APIs & Platforms
Summary
Build with Google's multimodal Gemini models via API and AI Studio
AI coding agent with deep Context Engine for large enterprise codebases
Google Gemini API

Google Gemini API Pros & Cons

Pros

  • Genuinely native multimodal models covering text, image, video, and audio in one API
  • Google AI Studio offers a real, usable free prototyping environment with no billing account required
  • Google Search and Google Maps grounding help reduce hallucinations with live information
  • Batch API and Flex pricing modes offer substantial cost savings for non-latency-sensitive workloads
  • Clear upgrade path from free prototyping to enterprise-grade deployment via the Gemini Enterprise Agent Platform

Cons

  • Pricing structure is complex, with per-model, per-mode (Standard/Batch/Flex/Priority) rates that require careful reading to estimate real costs
  • Free tier usage is used to improve Google's products, so privacy-sensitive projects need to upgrade to the Paid tier for that guarantee to apply
  • Frequent model churn (previews, deprecations, shutdown dates) means integrations need occasional migration work to stay current
  • Full enterprise-grade features like fine-tuning, VPC Service Controls, and CMEK live on the separate Gemini Enterprise Agent Platform, not the Developer API itself
  • Advanced capabilities like Computer Use and some agent tooling remain in preview with more restrictive rate limits
Augment Code

Augment Code Pros & Cons

Pros

  • Deepest codebase context of any AI coding tool — Context Engine indexes 400K+ files with semantic graphs, not just open tabs
  • #1 on SWE-bench Pro at 51.80% (Auggie CLI) — top publicly benchmarked coding agent score at publication
  • First and only AI coding assistant with ISO/IEC 42001 certification alongside SOC 2 Type II and CMEK
  • Usage-based flat pricing ($100/mo for up to 50 seats) is more predictable than per-seat models for variable teams
  • Cosmos platform covers the full SDLC — from ticket to PR, code review, tests, incidents, migrations, and onboarding
  • Trusted by Adobe, MongoDB, Webflow, Snyk, Pure Storage, Crypto.com, Tekion, and DXC across enterprise codebases

Cons

  • No free individual tier — Business plan starts at $100/month with a team minimum; sole developers pay full price for low usage
  • Pricing changed three times in 18 months (2023–2025), causing some developer community backlash and unpredictability concerns
  • IDE support limited to VS Code and JetBrains — no standalone IDE, no Neovim full feature parity, no Visual Studio
  • Closed-source with no self-hosting option — all computation runs on Augment's infrastructure or Enterprise cloud tenants
  • Context Engine first-run indexing takes 15–30 minutes on large repos before initial suggestions become fully accurate
  • Enterprise plan requires sales contact for pricing — no public list price above the Business tier